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Patrick Wickenhauser

dblp:210/5390 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Rendering · 87% Visualization and visual analytics · 13%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Rendering
antialiasing
0.312018
Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data · IEEE Trans. Vis. Comput. Graph. 2018
Rendering
particle rendering
0.312018
Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data · IEEE Trans. Vis. Comput. Graph. 2018
Rendering
relighting
0.312018
Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data · IEEE Trans. Vis. Comput. Graph. 2018
Rendering
shading
0.312018
Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data · IEEE Trans. Vis. Comput. Graph. 2018
Visualization and visual analytics › scientific visualization
molecular visualization
0.112018
Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data · IEEE Trans. Vis. Comput. Graph. 2018
Visualization and visual analytics
scientific visualization
0.112018
Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data · IEEE Trans. Vis. Comput. Graph. 2018

Methods — techniques the papers use, named apart from their topics

screen-space normal distribution function · 0.3mipmap caching · 0.3
YearPublicationVenuePosition
2018 Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data
abstract
Molecular dynamics (MD) simulations are crucial to investigating important processes in physics and thermodynamics. The simulated atoms are usually visualized as hard spheres with Phong shading, where individual particles and their local density can be perceived well in close-up views. However, for large-scale simulations with 10 million particles or more, the visualization of large fields-of-view usually suffers from strong aliasing artifacts, because the mismatch between data size and output resolution leads to severe under-sampling of the geometry. Excessive super-sampling can alleviate this problem, but is prohibitively expensive. This paper presents a novel visualization method for large-scale particle data that addresses aliasing while enabling interactive high-quality rendering. We introduce the novel concept of screen-space normal distribution functions (S-NDFs) for particle data. S-NDFs represent the distribution of surface normals that map to a given pixel in screen space, which enables high-quality re-lighting without re-rendering particles. In order to facilitate interactive zooming, we cache S-NDFs in a screen-space mipmap (S-MIP). Together, these two concepts enable interactive, scale-consistent re-lighting and shading changes, as well as zooming, without having to re-sample the particle data. We show how our method facilitates the interactive exploration of real-world large-scale MD simulation data in different scenarios.
Mohamed Ibrahim 0006, Patrick Wickenhauser, Peter Rautek, Guido Reina, Markus Hadwiger
IEEE Trans. Vis. Comput. Graph.2